Special Issue "Entropy and Information"

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A special issue of Entropy (ISSN 1099-4300).

Deadline for manuscript submissions: 30 August 2009

Special Issue Editors

Guest Editor
Dr. Peter Harremoës ^*
Centrum voor Wiskunde en Informatica, Kruislaan 413, NL-1098 SJ Amsterdam, The Netherlands
Website: http://homepages.cwi.nl/~ph/
E-mail:
^* Dr. Harremoës also serves as the Editor-in-Chief of Entropy

Special Issue Information

Submission

All papers should be submitted to entropy@mdpi.org with copy to the guest editor. To be published continuously until the deadline and papers will be listed together at the special websites. Both, research articles and review articles are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editors for announcment on this website.

Submitted papers should not have been published previously, nor be under consideration for publication elsewhere. All papers are refereed through a peer-review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Instructions for Authors page. Entropy is an international peer-reviewed quarterly journal published by Molecular Diversity Preservation International.

Please visit the Instructions for Authors page before submitting a paper. Open Access publication fees are 800 CHF per paper. English correction fees (250 CHF) will be added in certain cases (1050 CHF per paper for those papers that require extensive additional formatting and/or English corrections.).

Keywords

entropy, information, information theory

Planned Papers

Manuscript ID: Entropy-00-119
Type: Article
Title: Fast Fusion of Information
Authors: Michele Pappalardo
Abstract: In many applications, the management of uncertainty involves the combination of belief. The oldest method for the modelling of degrees of belief is the Bayesian that uses probability functions. The DS theory is a method of dealing with uncertainty providing a useful framework for the representation of information about a variable whose value is uncertain. The probabilities model of DS theory generalizes the Bayesian approach. The weights associated with the focal elements can be viewed as probabilities. The DS rule of combination has been the most controversial part of the theory. In particular Zadeh has reached a conjecture on the non-combinability of evidence from model of the DS theory. In this paper, for obtaining Bayesian masses, we consider this problem from a different perspective, starting from Yager’s model, using Jaynes’ MaxEnt principle as tool for redistributing masses in conflict to the focal elements. The result is a new fast way for fusing two independent, equally and reliable sources of evidence

Published Papers

No papers have been published in this special issue yet.

Last update: 6 October 2008